Speech recognition method and system

ABSTRACT

The present invention relates to a speech recognition method and a system for a speech-controllable telephone in which a value is computed (2) for a reference word with a speech recognizer (8) on the basis of a word uttered by a user, and a recognition resolution (6a, 6b) is made on the basis of said value. Prior to making said recognition resolution, it is found out (3) if repetition of a previous word is in question, and if so, a new value is computed (5) for the reference word on the basis of the value computed by the speech recognizer and of a value in the memory, computed earlier for the reference word, and a recognition resolution (6a, 6b) is made on the basis of said computed new value.

This is a continuation of application Ser. No. 08/072,145 filed of Jun.4, 1993, now abandoned.

BACKGROUND OF THE INVENTION

The present invention relates to a speech recognition method and system,in particular to a method and system for a voice-controllable telephonein which a value of a reference word is computed by a speech recognizeron the basis of a word uttered by a user, and a recognition resolutionis made on the basis of that value.

BRIEF DESCRIPTION OF THE PRIOR ART

Telephones are usually provided with a handset which the user holds inhis/her hands while speaking. This is also the case when radiophonessuch as mobile phones are used. Such a telephone leaves only one handfree, and thus can cause difficulties when driving. A solution to thisproblem is a separate microphone placed in the car and a separateloudspeaker to be controlled at an appropriate volume and located at anappropriate distance from the user so that the user is able to hear theother party clearly. Even with this design the user has to use one ofhis hands to make a call, i.e. in dialling the number of the other partyor in responding to an incoming call, or in terminating a call.

For a telephone user to be able to concentrate on driving, so-calledhands free telephones have been developed in which the operations can bevoice controlled. Hereby, all of the telephone operations can be voicecontrolled, such as on/off switching, transmit/receive, speech volumecontrol, phone number dialling, telephone call answering, and the useris thus able to concentrate on driving. The driver need not remove hishands from the steering wheel nor take his eyes from the road;therefore, the hands free-telephone considerably increases road safety.

A drawback involved in the voice-controlled phone is that speechrecognition is not entirely perfect. The background noise caused by thevehicular environment is high and thus, speech recognition becomes moredifficult. Some endeavours have been made to market the speechrecognition ability in association with mobile phones, but because ofthe unreliability thereof the users' interest in voice-controlled phoneshas been insignificant. The recognition accuracy of speech recognizersknown in the art is not very good, particularly in adverse conditions,e.g. in a moving vehicle where the high background noise substantiallypresents reliable word recognition. Incorrect recognition resolutionsgenerally cause most of the inconveniences in implementing a usercommunications system because they might start undesirable operations,such as termination of calls in the middle thereof, which isparticularly inconvenient from the user's point of view. The most commonconsequences of erroneous speech interpretations is dialling a wrongnumber. For this reason, user communications are designed so that arecognition resolution is not made by a speech recognizer at all if ithas not achieved a sufficient ensurance of the word uttered by the user,and in such instances, the user is usually requested to repeat thecommand uttered.

Nearly all speech recognizers are based on the performance principlethat a word uttered by a user is compared by a rather complicated methodwith reference words previously stored in the memory of the speechrecognizer. Speech recognizers generally compute a number correspondingto each reference word and indicating to what extent the word uttered bythe user resembles the reference word. Finally, a recognition resolutionis made on the basis of the numbers so that the reference word which theuttered word most resembles is chosen for the resolution. One of themost well known methods in the comparison between the uttered word andthe reference words is the Dynamic Time Warping (DTW) method and thestatistical Midden Markow Model method (HMM).

In both the DTW and the HMM method an unfamiliar speech pattern iscompared with the known reference patterns. In the Dynamic Time Warping,a speech pattern is divided into a number of frames and the localdistance between the speech part in each frame and the speech partequivalent to the reference pattern is computed. On the basis of thelocal distances derived in this manner a minimum path is looked forbetween the initial and terminating point of the word by means of a DTWalgorithm. Thus, with a Dynamic Time Warping a distance can be obtainedbetween the uttered word and the reference words. In the method speechpatterns are generated, and said speech pattern generation step ispatterned with a status change pattern according to the Markov Method.Said status change pattern is thus HMM. Speech recognition for saidreceived speech patterns now takes place by defining the observationprobability for said speech patterns with the aid of the HMM pattern.Using the HMM in speech recognition, an HMM pattern is first generatedfor each word to be recognized, i.e. for each reference word. The HMMpatterns are stored in the memory of the speech recognizer. After thespeech recognizer receives the speech pattern, an observationprobability is computed for each HMM pattern stored in the memory, andas the result of the recognition process, a word is provided for the HMMpattern for which the highest observation probability is obtained. Inother words, such probability is computed for each reference word withwhich it would be the word uttered by the user. The highest observationprobability mentioned above describes the equality of the speech patternreceived and the closest HMM pattern, i.e. the closest reference speechpattern.

Thus, in current systems the speech recognizer computes a certain numberfor the reference words on the basis of the word uttered by a user; inthe DTW system the number is the distance between words, and in the HMMmethod the number indicates a probability of the equality of the words.When using the HMM method, a given threshold probability is usuallydefined for the speech recognizers which the most probable referenceword has to reach in order to make a recognition resolution. Anotherfactor affecting the recognition resolution could be e.g. a differencebetween the probabilities of the most probable word and the second mostprobable word; it is expected to be great enough so that a recognitionresolution can be made. When a recognition resolution is being made onthe basis of the recognition probability of the most probable word, theerring probability is allowed to be at most e.g. 0.1. It Is thereforepossible that when the background noise is great, for a reference wordin the memory, such as reference word "one", the greatest probability isobtained in every attempt on the basis of a command uttered by the userto be e.g. a 0.8 probability compared with the other reference words.Since the probability remains below the threshold probability 0.9, thisis not accepted and the user may have to utter the command several timesbefore exceeding the recognition probability limit, and the speechrecognizer accepts the command although the probability may have beenvery close to the accepted value. From the point of view of the user,this is most disturbing. A correct recognition result can be achievedwith a first attempt using the present technique quite often when thespeed of the car is below 80 to 90 km per hour depending on the soundinsulation of the car and the user's manner of speaking. At higherspeeds the performance of the recognizer, however, reduces veryabruptly, and in most cars the speech recognizer no longer operatessufficiently reliably at speeds over 100 km per hour to be regardeduseful. It is particularly at said speeds at which the need to increasethe safety in the traffic is greater than at lower speeds.

SUMMARY OF THE INVENTION

In accordance with a first aspect of the invention there is providedSpeech recognition apparatus comprising, comparing means for comparing afirst word uttered by a user with an at least one predeterminedreference word, calculating means for calculating a value correspondingto the similarity between the first word uttered by the user and the atleast one predetermined reference word, and selecting means forselecting said value in accordance with a predetermined criterion,wherein the calculating means is capable of utilising said value incalculating a new value corresponding to the similarity between a secondword uttered by the user and the at least one reference word.

In accordance with a second aspect of the invention there is provided aspeech recognition method comprising, comparing a first word uttered bya user with an at least one predetermined reference word, calculating avalue corresponding to the similarity between the first word uttered bythe user and the at least one predetermined reference word, andselecting said value in accordance with a predetermined criterion,wherein said value is used to calculate a new value corresponding to thesimilarity between a second word uttered by the user and the at leastone reference word.

The first and second aspect of the invention have the advantage that amore reliable recognition of words is possible, even if the similaritybetween uttered words and reference words is not high.

In accordance with a third aspect of the invention there is providedspeech recognition apparatus comprising, comparing means for comparing afirst word uttered by a user with predetermined reference words,calculating means for calculating values corresponding to the similaritybetween the first word uttered by the user and respective predeterminedreference words, and selecting means for selecting one of said values inaccordance with a predetermined criterion, wherein the calculating meansis capable of utilising a selected value in calculating new valuescorresponding to the similarity between a repeated utterance by the userof said first word and the reference words, and the predeterminedcriterion is that the difference between a highest value and a nexthighest value exceeds a predetermined threshold value.

In accordance with the fourth aspect of the invention there is provideda speech recognition method comprising, comparing a first word utteredby a user with predetermined reference words, calculating valuescorresponding to the similarity between the first word uttered by theuser and respective predetermined reference words, and selecting saidvalue in accordance with a predetermined criterion, wherein a selectedvalue is used to calculate new values corresponding to the similaritybetween a repeated utterance by the user of said first word and thepredetermined reference words and the predetermined criterion is thatthe difference between a highest value and a next highest value exceedsa predetermined threshold value.

The third and fourth aspects of the invention have the advantage thatmore than one voice controlled function can be utilised in apparatuscomprising the invention. This has the advantage that further utterancesand calculations are necessary only when an uttered word cannot bereliably recognised, or when an uttered word is similar to two differentreference words.

In a preferred embodiment of the first and second aspects of theinvention, the second word uttered by the user is the same as the firstword uttered by the user. This has the advantage that a secondcalculation is only performed when the second uttered word is the sameas the first uttered word, thereby avoiding unnecessary delay inrecognising uttered words.

Preferably, the predetermined criterion is that said value is less thana predetermined threshold value. This has the advantage that furtherutterances and calculations are necessary only when an uttered wordcannot be reliably recognised, or when an uttered word is similar to twodifferent reference words.

Suitably, repetition of the first word uttered by the user is requestedwhen said value does not fulfil said predetermined criterion whichclearly indicates to the user that an uttered word has not beenrecognised and that it is necessary for the user to repeat the word.

In the method of the invention, a speech recognizer computes therecognition probabilities for reference words and makes a recognitionresolution if one of the probabilities exceeds a predetermined thresholdvalue; otherwise, the user is requested to utter the word again and arecognition resolution is made thereon if the probability of one of thereference words exceeds a predetermined threshold value: otherwise, anew probability is computed utilizing the prevailing probabilitycomputed by the speech recognizer, and a probability computed in one ormore preceding times, on the condition that they are probabilities ofone and the same reference word, and that a recognition resolution ismade if said probability exceeds a predetermined threshold value. Unlessthe predetermined threshold value is exceeded by the probabilitycomputed by the speech recognizer, the computed probability is stored inthe memory, the user is requested to utter the word once again, and thevalue stored in the memory Is used together with the subsequentprobability / probabilities computed for the same word by the speechrecognizer, in order to compute a new probability to be computed on thebasis of said probabilities (for making a recognition resolution if,taking in consideration the preceding probabilities, a thresholdprobability is achieved). Thereafter, when the speech recognizercomputes a probability exceeding the threshold value, or it is reachedby taking in consideration the preceding probabilities, the memory isreset. Also in the instance in which a repetition of a previous word isin question, the memory is reset prior to a recognition resolution. Thememory is reset also when the power is switched on in the apparatus andif an operation is interrupted.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 shows a principle flow diagram of the steps to be taken in themethod, and

FIG. 2 shows a block diagram for implementing the method in a system inwhich speech recognition is used.

DETAILED DESCRIPTION OF EMBODIMENTS OF THE INVENTION

In FIG. 1 the speech recognition method of the invention is clarified.The method is not directly associated with the internal method of thespeech recognizer used in speech recognition, but by using the methodachieving a recognition resolution is accelerated and the recognitionprecision is improved without paying attention to the properties of theactual speech recognizer. When the power is switched on in the means atthe "beginning" 1 of the process, the memory is reset and an utterancefrom a user is expected to take place, whereby the speech recognizercomputes 2 probabilities for all reference words and, as a result ofrecognition, it yields the reference word possessing the greatestprobability, i.e. the reference word resembling most the word uttered bythe user. If the probability of the reference word does not exceed apredetermined threshold value or the threshold value of theprobabilities of the most probable and the second most probable word, inthe present context called commonly the threshold values of speechrecognition, it is found out 3 if the word being examined is arepetition of the preceding word. If repetition of such preceding wordis not in question, the memory is reset 4a. When the user has notuttered the word more than once, the memory contains nothing during thefirst computation round, whereby no new probability is computed, either,but a recognition resolution is made 6a, and if no reliable recognitioncan be made 6b, a probability computed by the speech recognizer isstored 7 in the memory, and a subsequent utterance from the user isawaited. If, on the other hand, the word is a repetition of the previousword, a new probability is computed 5 making use in the computation ofthe probability of a preceding recognition attempt stored in the memory,and on the basis thereof, a recognition resolution is made 6a, 6b. Ifthe new probability is obtained by means of the computations 5 exceedsthe threshold value, i.e. a reliable recognition can be made 6b, thememory is reset 4b, and a subsequent utterance 2 from the user and arecognition result obtained 2 from the speech recognizer are expected totake place, etc. If the new probability is below the threshold value, sothat no reliable recognition can be made, said new probability is storedin the memory 7, and a subsequent utterance 2 of the user is expected totake place, etc. If one of the functions is interrupted, the memory isreset, so that nothing that would distort a new recognition to bestarted after the interruption remains there. The method according tothe invention may also be implemented so that the recognition resolution6a, 6b is made before finding out 3 whether a repetition of thepreceding word is in question or not. Now, if the value computed by thespeech recognizer for the repeated word exceeds the set threshold value,no such computation of a new probability needs to be done in which thevalues computed in preceding recognition attempts are taken intoaccount.

For carrying out the computation process, several computation procedurescan be developed, by using which a more appropriate probability can beprovided through the use of the preceding probability in suchcomputations. However, the most useful formula is the computationformula for conditional probability. For demonstrating the computationprocedure used in the method, the utilisation of conditional probabilitycomputation is described below in detail and in conjunction with themethod of the invention. Such a computation is examined for a situationin which a user utters first a word A and then word B after the user hasbeen requested by the system to repeat that word. A speech recognizercomputes e.g. the following probabilities for both words A and B:

P(A=1)=0.7 (probability that A was "one")

P(A=2)=0.3 (probability that A was "two")

P(B=1)=0.8 (probability that B was "one")

P(B=2)=0.2 (probability that B was "two")

If 0.9 has been set for the threshold value of the recognitionresolution, no recognition resolution can be made concerning eitherrecognition. When we know that the user uttered the same word bothtimes, the reliability of the recognition can be increased by utilizingthe probability computed by one Or more of the preceding and presentrecognitions in order to compute a new probability. This can be donee.g. with a conditional probability computation as follows: ##EQU1## Theabove computation in which a probability was computed for the particularthat the second word, i.e. B, is "one" on the condition that A is equalto B, in other words, the first word is the same as the second one,leads to a new probability which in the present case exceeds thethreshold value, and a recognition resolution can be made. Even if thenew probability did not exceed the threshold value, it is, however,better than the individual probability computed by the speechrecognizer, and in this manner said new probability is stored in thememory and used in calculating a subsequent new probability togetherwith a subsequent probability computed by the speech recognizer. It isalso found that the difference with the second most probable wordincreases. The above formula can be simplified by using only thenumerator instead of the denominator and multiplied with an appropriateconstant Y:

    P(B=x|A=B)=Y*P(A=x and B=x)=Y*P(A=x)*P(B=x)

Thus, if the user utters a word N times, the total probability of eachreference word r is obtained as follows:

    P(r)=Y*P(r,2)* . . . P(r,N)

where P(r, 1) is the first utterance of reference word r, P(r,2) is thesecond and N is the last utterance thereof. In the above example aprobability for a given reference word was computed. In conformance withthe threshold criteria of speech recognition, the difference of theprobabilities of two reference words (of the reference word whichobtained the highest probability and the second highest probability fromthe speech recognizer), automatically increases and therefore therecognition reliability is improved. It is simple to use the abovemethods of computation when the HMM method is used in the speechrecognizer because in such instances it computes for each reference wordthe probability of the word uttered by the user. When using the DTWmethod, the computation is not quite so straightforward because now aprobability is not computed for reference words in the speechrecognizer, but a distance or a standard of how far the uttered word isfrom each reference word.

Therefore, in order to improve the recognition reliability according tothe method of making use of prior probabilities, the standard ordistance has first to be transformed into a probability. In DTW it isthus possible to describe with a number D(r,i) to what extent eachreference word r resembles an uttered word in a repeated time i. Hereby,a probability can be computed from the number with the aid of a functionf(), e.g. a non-linear function, as follows:

    D(r)=f(D(r,1),D(r,2), . . . ,D(r,N))

Alternatively an estimate of the probability of a reference word fromthe result yielded by a DTW algorithm by means of an estimate g(),whereby the result computed by the speech recognizer can be convertedinto a probability and the probability of an i:nth repetition ofreference word r is now P(r,i)=g(D(r,i)) whereby the number P(r,i), canbe used according to the method in calculating a new probability asdescribed above.

One way of implementing the method of the invention in the speechrecognition system is shown in FIG. 2. With the method, the recognitionaccuracy of the speech recognition system can be improved in which thespeech recognizer 8 provides recognition results, i.e. recognitionprobabilities, which are fed to the recognition results processing unit9. Each recognition results contains a list of the words to berecognized, for each of which a probability (or other quality factor)has been computed, describing to what extent a word uttered by the userbears resemblance to each reference word. The reference words may havebeen stored in advance in the internal reference word memory of thespeech recognizer 8 or the speech recognizer has been made able to"learn" words uttered by the user. However, this detail has no bearingfrom the point of view of the invention on how and when the referencewords have been stored in the reference word memory, and the speechrecognizer 8 need not have a reference word memory. If a word cannot berecognized at a sufficient reliability, the user communications device11 requests the user to repeat the word. In such instance, the usercommunications device 11 gives information to the processing block 9, ofthe recognition results on whether a word is going to be repeated by theuser or not. When the user communications device 11 informs theprocessing unit 9 that a repetition of a word is to be expected, thedata stored in conjunction with the preceding recognition attempt areaccessed from the memory 10, and new probabilities are computed for thereference words in a manner regarding the preceding values according tothe invention. If no sufficiently reliable recognition can be made, evenbased on the new probabilities, said new, higher calculatedprobabilities are nevertheless stored in the memory 10. After asuccessful recognition has been made, the memory 10 is reset. The memoryis also reset when data is sent to the processing block 9 from the usercommunications device 11 that the next word to enter is not the same asthe previous one. In practice, the system may be such that theprocessing block 9, the memory 10 and the user communications block 11form part of the same processor, i.e. they are realized with the aid ofa processor. The processor can be one arranged particularly for thespeech recognition system or it may be the main processor for aradiophone. Typically, also the speech recognizer 8 comprises a signalprocessor.

With the aid of the present invention, the speech recognition accuracycan be improved although the basic performance of the speech recognizeritself is not improved. When the recognition accuracy is improved, thedecision making concerning recognition is accelerated and a more userfriendly hands free phone can be implemented. The present invention isnot limited to the formula of the example shown in FIG. 1 but variousfunctions may also be performed in a different order.

In view of the foregoing description it will be evident to a personskilled in the art that various modifications may be made within thescope of the invention.

The scope of the present disclosure includes any novel feature orcombination of features disclosed therein either explicitly orimplicitly or any generalisation thereof irrespective of whether or notit relates to the claimed invention or mitigates any or all of theproblems addressed by the present invention. The applicant hereby givesnotice that new claims may be formulated to such features during theprosecution of this application or of any such further applicationderived therefrom.

I claim:
 1. Speech recognition apparatus, comprising:word recognitionmeans operative during a word recognition mode of operation forcomparing a first word uttered by a user with a predetermined referenceword and for outputting a respective first value that indicates anamount of similarity between the first word uttered by the user and arespective predetermined reference word; processing means having aninput coupled to an output of said word recognition means for receivinga respective first value that is outputted by said word recognitionmeans in response to said first word uttered by the user; memory meanscoupled to said processing means, said processing means being responsivefor storing the respective first value in said memory means upon anoccurrence of a condition such that a respective first value is lessthan a predetermined threshold value, said processing means determininga revised first value when a respective second value is outputted fromsaid word recognition means in response to the user uttering a secondword, the revised first value being determined from the respectivesecond value and from the stored respective first value, said revisedfirst value indicating an amount of similarity between the second worduttered by the user and the respective predetermined reference word thatis associated with said revised first value; and indicator meansresponsive to a condition such that a respective or revised value isequal to or greater than a predetermined threshold value, for indicatingthat said second word uttered by the user corresponds to the respectivepredetermined reference word.
 2. Speech recognition apparatus as setforth in claim 1 wherein said processing means further includes:meansresponsive for storing the revised first value in said memory means uponan occurrence of a condition such that the revised first value is lessthan the predetermined threshold value, said processing means furtherdetermining a second revised first value when a respective third valueis outputted from said word recognition means in response to the useruttering a third word, the second revised value being determined fromthe respective third value and from the stored revised value, saidsecond revised value indicating an amount of similarity between thethird word uttered by the user and the respective predeterminedreference word that is associated with said stored revised value, saidindicator means being further responsive to a condition such that asecond revised value is equal to or greater than the predeterminedthreshold value, for indicating that the third word uttered by the usercorresponds to the respective predetermined reference word.
 3. Speechrecognition apparatus as set forth in claim 2, wherein said processingmeans further includes:means for determining a conditional probabilityfor use in determining the stored revised value and the second revisedvalue.
 4. Speech recognition apparatus as set forth in claim 1 whereinsaid word recognition means has an input coupled to an output of aspeech transducer that is located within a vehicle.
 5. Speechrecognition apparatus, comprising:word recognition means operativeduring a word recognition mode of operation for comparing a first worduttered by a user with a plurality of predetermined reference words andfor outputting a plurality of respective first probability valuesindividual ones of which indicate an amount of similarity between thefirst word uttered by the user and a respective one of said plurality ofpredetermined reference words; processing means having an input coupledto an output of said word recognition means for receiving a plurality ofrespective first probability values that are outputted by said wordrecognition means in response to said first word uttered by the user,said processing means including means for obtaining differences betweenthe respective first probability values and responsive to a conditionsuch that a difference between (a) a first respective first probabilityvalue of said plurality of respective first probability values that hasthe highest value and (b) a second respective first probability value ofsaid plurality of respective first probability values that has thesecond highest value, is less than a predetermined threshold value, forstoring said first and second respective first probability values;memory means coupled to said processing means, said processing meansbeing responsive for storing the first respective first probabilityvalue and the second respective first probability value in said memorymeans upon the occurrence of said condition, said processing meansdetermining a revised first respective first probability value and arevised second respective first probability value when a secondplurality of respective second probability values are outputted fromsaid word recognition means in response to the user uttering a secondword, the revised first respective first probability value and therevised second respective first probability value being determined fromthe second plurality of respective second probability values and fromthe stored first and second respective first probability values; andindicator means responsive to a condition such that a difference betweenthe revised first respective probability value and the revised secondrespective probability value or a first respective probability value anda second respective probability value is equal to or greater than thepredetermined threshold value, for indicating that said second worduttered by the user corresponds to a respective one of said plurality ofpredetermined reference words that has the highest respective or revisedprobability value associated therewith.
 6. Speech recognition apparatusas set forth in claim 5 wherein said processing means furtherincludes:means for determining a conditional probability for use indetermining the revised respective first probability values.
 7. Speechrecognition apparatus as set forth in claim 5 wherein said processingmeans further includes:means for determining a conditional probabilityfor use in determining the revised respective first probability values.8. Speech recognition apparatus, comprising:word recognition meansoperative during a word recognition mode of operation for comparing aword uttered by a user with a plurality of predetermined reference wordsand for outputting a plurality of respective first values respectiveones of which indicate an amount of similarity between the first worduttered by the user and a respective one of said plurality ofpredetermined reference words; processing means having an input coupledto an output of said word recognition means for receiving a plurality ofrespective first values that are outputted by said word recognitionmeans in response to a first word uttered by the user, said processingmeans including means for transforming said plurality of respectivefirst values into a corresponding plurality of respective firstprobability values, said processing means including means for obtainingdifferences between the respective first probability values andresponding to a condition such that a difference between (a) a firstrespective first probability value of said plurality of respective firstproability values that has the highest value and (b) a second respectivefirst probability value of said plurality of respective firstprobability values that has the second highest value, is less than apredetermined threshold value, for storing said first and secondrespective first probability values; memory means coupled to saidprocessing means, said processing means being responsive for storing thefirst respective first probability value and the second respective firstprobability value in said memory means upon the occurrence of saidcondition, said transforming means also transforming a second pluralityof respective second values outputted from said Word recognition meansin response to the user uttering a second word into a correspondingsecond plurality of respective second probability values, saidprocessing means determining a revised first respective firstprobability value and a revised second respective first probabilityvalue from the plurality of respective second probability values and thestored first and second respective first probability values, in responseto the user uttering the same word a second time; and means responsiveto a condition such that a difference between the revised firstrespective first probability value and the revised second respectivefirst probability value is equal to or greater than a predeterminedthreshold value, for indicating that said second word uttered by theuser corresponds to a respective one of said plurality of predeterminedreference words that has the highest respective or revised firstprobability value associated therewith.
 9. Speech recognition apparatusas set forth in claim 8 wherein said processing means furtherincludes:means for use in determining a conditional probability fordetermining the revised respective first probability values.
 10. Speechrecognition apparatus as set forth in claim 8 wherein said wordrecognition means has an input coupled to an output of a speechtransducer that is located within a vehicle.
 11. A speech recognitionmethod, comprising the steps of:during a word recognition mode ofoperation; comparing a first word uttered by a user with a plurality ofpredetermined reference words and outputting a respective first valuethat indicates an amount of similarity between the first word uttered bythe user and a respective one of said plurality of predeterminedreference words; responding to a condition such that a first respectivevalue is less than a predetermined threshold value, by storing the firstvalue in a memory means; responding to a respective second valueoutputted in response to the user uttering a second word, by determininga revised first value, from the respective second value and from thestored respective first value, said revised first value indicating anamount of similarity between the second word uttered by the user and therespective one of said plurality of predetermined reference words thatis associated with said revised first value; and responding to acondition such that the revised first value is equal to or greater thana predetermined threshold value, by indicating that the second worduttered by the user corresponds to the respective one of said pluralityof predetermined reference words.
 12. A method as set forth in claim 11and further including the steps of:responding to a condition such thatthe revised first value is less than the predetermined threshold value,by storing the revised first value in the memory means; responding to athird respective value outputted in response to the user uttering athird word, by determining a second revised first value, from the thirdrespective value and the stored revised first value, said second revisedfirst value indicating an amount of similarity between the third worduttered by the user and the one of said plurality of predeterminedreference words that is associated with said stored revised value, and;responding to a condition such that the second revised first value isequal to or greater than a predetermined threshold value, by indicatingthat the third word uttered by the user corresponds to the respectiveone of said plurality of predetermined reference words.
 13. A method asset forth in claim 12 wherein the step of determining a first revisedfirst value and the step of determining a second revised first valueeach include a step of determining a conditional probability.
 14. Amethod as set forth in claim 11 wherein the step of comparing includes astep of inputting a signal from an output of a speech transducer that islocated within a vehicle.
 15. A speech recognition method, comprisingthe steps of:during a word recognition mode of operation; comparing afirst word uttered by a user with a plurality of predetermined referencewords and outputting a plurality of respective first probability valuesindividual ones of which indicate an amount of similarity between thefirst word uttered by the user and a respective one of said plurality ofpredetermined reference words; responding to a condition such that adifference between (a) a first respective first probability value of oneof the plurality of respective first probability values that has thehighest value and (b) a second respective first probability value ofsaid plurality of respective first probability values that has thesecond highest value, is less than a predetermined threshold value, bystoring at least the first respective first probability value and thesecond respective first probability value in a memory means; respondingto a plurality of respective second probability values outputted inresponse to the user uttering a second word, by determining a revisedfirst respective first probability value and a revised second respectivefirst probability value from the plurality of respective secondprobability values and the stored first and second respective firstprobability values; and responding to a condition such that a differencebetween the revised first respective first probability value and therevised second respective first probability value is equal to or greaterthan a predetermined threshold value, for indicating that the secondword uttered by the user corresponds to a respective one of saidplurality of predetermined reference words that has the highest revisedfirst probability value associated therewith.
 16. A method as set forthin claim 15 wherein the step of determining a revised first respectivefirst probability value and a revised second respective firstprobability value includes a further step of determining a conditionalprobability.
 17. A method as set forth in claim 15 wherein the step ofcomparing includes a step of inputting a signal from an output of aspeech transducer that is located within a vehicle.
 18. A speechrecognition method, comprising the steps of:during a word recognitionmode of operation; comparing a first word uttered by a user with aplurality of predetermined reference words and outputting a plurality ofrespective first values respective ones of which indicate an amount ofsimilarity between the first word uttered by the user and a respectiveone of said plurality of predetermined reference words; transformingsaid plurality of respective first values into a corresponding pluralityof respective first probability values; responding to a condition suchthat a difference between (a) a first respective first probability valueof said plurality of respective first probability values that has thehighest value and (b) a second respective first probability value ofsaid plurality of respective first probability values that has thesecond highest value, is less than a predetermined threshold value, bystoring said first and second respective probability values in a memorymeans; responding to a plurality of respective second values outputtedfrom the word recognition means in response to the user uttering asecond word, by transforming the plurality of respective second valuesinto a corresponding plurality of respective second probability values;determining a revised first respective first probability value and arevised second respective first probability value from the plurality ofrespective second probability values and the stored first and secondrespective first probability values; and responding to a condition suchthat a difference between the revised first respective first probabilityvalue and the revised second respective first probability value is equalto or greater than a predetermined threshold value, by indicating thatsaid second word uttered by the user corresponds to a respective one ofsaid plurality of predetermined reference words that has the highestrespective or revised probability values associated therewith.
 19. Amethod as set forth in claim 18 wherein the step of determining arevised first respective first probability value and a revised secondrespective first probability value further includes a step ofdetermining a conditional probability.
 20. The method as set forth inclaim 18 wherein the step of determining a revised first respectivefirst probability value and a revised second respective firstprobability value further includes a step of determining a conditionalprobability.
 21. A hands-free radiotelephone, comprising:wordrecognition means having an input coupled to an output of a speechtransducer that is located within a vehicle, said word recognition meansbeing operative during a word recognition mode of operation forcomparing a first word uttered by a user with a plurality ofpredetermined reference words and for outputting a respective firstvalue that indicates an amount of similarity between the first worduttered by the user and a respective one of said plurality ofpredetermined reference words; processing means having an input coupledto an output of said word recognition means for receiving a respectivefirst value that is outputted by said word recognition means in responseto said first word uttered by the user; memory means coupled to saidprocessing means, said processing means being responsive for storing therespective first value in said memory means upon an occurrence of acondition such that a respective first value is less than apredetermined threshold value; means responsive to said condition forrequesting the user to repeat the first word, said recognition meansoutputting a respective second value in response to the user utteringsaid word, said processing means determining at least one revised firstvalue from said respective second value and said stored respective firstvalue, the revised first value indicating an amount of similaritybetween the first word uttered by the user, the second word uttered bythe user, and a respective one of said plurality of predeterminedreference words word selection means responsive to a condition such thata revised first value is equal to or greater than the predeterminedthreshold value, for selecting a respective one of said plurality ofpredetermined reference words as an input to a user-controlled functionof said radiotelephone.
 22. A method for dialing a telephone number witha hands-free radiotelephone, comprising the steps of:during a wordrecognition mode of operation of a speech recognition system; respondingto a user vocalizing a number between 0 and 9, by performing a wordrecognition function to determine a respective first probability valuethat the vocalized number is a respective first number between 0 and 9;if the respective first probability value is equal to or greater than apredetermined threshold value, identifying said respective first numberbetween 0 and 9 as the number vocalized by the user and using theidentified number as a part of the telephone number to be dialed; if therespective first probability value is less than the threshold value,storing the respective first probability value, and instructing the userto vocalize the same number a second time; responding to the userre-vocalizing the number between 0 and 9, by performing the wordrecognition function to determine a respective second probability valueindicating the amount by which the re-vocalized number is similar to arespective second number between 0 and 9; if the respective secondprobability value is equal to or greater than the threshold value,identifying said respective second number between 0 and 9 as the numbervocalized by the user the second time and using the identified number asa part of the telephone number to be dialed; if the respective secondprobability value is less than the predetermined threshold value,calculating a revised first probability value from the stored firstprobability value and the second respective probability value; if therevised first probability value is less than the threshold value,storing the revised first probability value, and instructing the user tovocalize the same number a third time; and if the revised firstprobability value is equal to or greater than the threshold value,identifying a number between 0 and 9 as the number vocalized by the userand using the identified number as a part of the telephone number to bedialed.